16 citations · 35 across the 5 of their papers we have counts for
4 papers · 1 filter
Helix: Holistic Optimization for Accelerating Iterative Machine Learning
Doris Xin, Stephen Macke, Litian Ma +3
Machine learning workflow development is a process of trial-and-error: developers iterate on workflows by testing out small modifications until the desired accuracy is achieved. Un…
Helix: Accelerating Human-in-the-loop Machine Learning
Doris Xin, Litian Ma, Jialin Liu +3
Data application developers and data scientists spend an inordinate amount of time iterating on machine learning (ML) workflows -- by modifying the data pre-processing, model train…
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities
Doris Xin, Litian Ma, Jialin Liu +3
Development of machine learning (ML) workflows is a tedious process of iterative experimentation: developers repeatedly make changes to workflows until the desired accuracy is atta…
Towards a Theory of Data-Diff: Optimal Synthesis of Succinct Data Modification Scripts
Tana Wattanawaroon, Stephen Macke, Aditya Parameswaran
This paper addresses the Data-Diff problem: given a dataset and a subsequent version of the dataset, find the shortest sequence of operations that transforms the dataset to the sub…